#BIGTHINK by Embiggen X: Have the Right Conversations on AI
2025 04.15 Edition
FRAMEWORKS AND PERSPECTIVESBuild on Your Strengths Using AI
Note: The following entries are based on the previous LinkedIn posts of one of our Firm’s Partners, Rolan Marco Garcia, who talks about Business AI, Digital Transformation and Enterprise Innovation.
Most conversations about AI transformation focus on efficiency. Cost savings. Process automation. Margin improvements. Important? Sure. But if that’s the only lens we're using, then we're missing the bigger opportunity because AI isn't just technology for doing the same things cheaper or faster.
AI is a capability for doing things differently in ways your competitors can't easily replicate. Think business model reinvention.
At Embiggen X we think that the real value of AI transformation shows up not just in your bottom line — but in your competitive advantage. As an Enterprise leader, you should think about:
Better, faster decision-making.
New customer experiences competitors can’t match.
Business models that didn’t exist before.
Teams that operate with augmented creativity and insight.
New capabilities that make you move faster.
AI should absolutely help your business run leaner. But the more strategic question that leaders should ask is:
How will it help you compete differently? How can it highlight your strengths and competitive advantages or build new strengths?
Efficiency keeps you in the game. Advantage is what helps you win it.
CASE STUDY FEATURETTEFix Your Data First
"Fix your data first" isn’t a suggestion—it’s a hard prerequisite for AI success.
We’ve seen initiatives across industries for large companies in APAC and the EU, and the pattern is clear: nearly 80% of failures can be traced back to poor data quality, accessibility, or governance.
Not bad models. Not bad algorithms. Just bad data.
Yet time and time again, companies rush into AI projects without getting their data house in order — convinced that powerful models can somehow compensate for incomplete, inconsistent, or siloed data. They can’t.
Trying to implement AI on broken data is like building a precision instrument with warped components—it might look functional, but it won’t work reliably (or at all). We’ve seen this play out in manufacturing, finance, healthcare. The companies that succeed invest 30-40% of their initial AI budget in data readiness—cleaning, structuring, and governing their data before layering AI on top. That investment pays off in better model performance, fewer failures, and faster ROI.
So why do so many companies resist fixing their data first?
Because data work is unglamorous. It’s not the headline-grabbing AI demo. It doesn’t feel like innovation. But skip this step, and you’re almost guaranteeing failure.
Embiggen X has worked with enterprises to address their data issues head on and consolidate various data from multiple siloed systems and sources. This includes making sure that data is clean and is in the right formats. Then disparate data is integrated into a data lake or warehouse.
AI & Data Leaders in enterprises, are you seeing the same challenges? What data roadblocks have slowed down your AI initiatives? We would love to hear your perspective.
INDUSTRY NEWS & EVENTS7 strategic insights for AI transformation from Enterprise Connect 2025 ZDNet
Generative AI is not the solution to every problem CSW
China, ASEAN media, think-tanks embrace AI Philippine News Agency
Reframing digital transformation through the lens of generative AI MIT Technology Review
ABOUT USEmbiggen X is an International Business AI & Data Transformation Firm for trailblazing CEOs and their organizations. We help the C-Suite become successful by harnessing the power of AI & Data to solve their most pressing issues.
​We also empower businesses by leveraging cutting-edge analytics to turn complex data into actionable insights and decisions, driving measurable economic and social impact across functional areas. Our clients today span both Europe and the Asia Pacific region.